Development and Validation of Brain Connectivity Analysis with Calcium Imaging Data

Abstract

The study of functional connectivity of the brain is significant in Neuroscience. The connectivity among neurons are started from several anatomical links such as synapses. This neural activity can be represented as cross-correlations, visualizing connections among neurons or with the flow of information. Brain connectivity analyses are essential to knowing how neurons and neural networks process information. It helps to reveal the pathological basis of neurological disorders and facilitates to find out the diagnosis process of brain diseases. The in vivo imaging of neuronal activity using calcium indicators has become fundamental in the latest research in neuroscience. In order to find out functional connectivity from the neuron-level, we proposed a calcium imaging based tool. Firstly, the fluorescence signal was measured from raw calcium imaging data using conventional computational methods such as motion artifact was controlled using the crosscorrelation method. The goal was to use these obtained time-series data from calcium imaging signals to infer the functional connectivity of the brain. Graph theory can be used for the mathematical study of networks and applied to analyze functional brain connectivity. Graph theory has already been applied in different ways in fMRI data but recently has started to find out microscopic functional networks of neurons by using calcium imaging data. In this research, we found out the graph measures and structures of neuronal networks with calcium imaging data by implementing a MATLAB-based toolbox. However, this system was designed to use for fMRI data. The obtained result from calcium imaging data was processed and organized to analyze functional connectivity. Initially, artificial in vivo two-photon calcium imaging movie datasets were generated and used to investigate the feasibility of this adopted approach. Finally, a real in vivo two-photon calcium imaging dataset was applied successfully to investigate the alterations of the measures of functional connectivity in terms of the behavioral test.